Preventing Face-Based Authentication Spoofing

1. A system to prevent face-based authentication spoofing, the system comprising: an emitter controller to control a visible light emitter to project a pattern into a field of view for a camera during an authentication attempt using a face; an image sampler to obtain an image from the camera for the authentication attempt; and a spoofing detection controller to: identify a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image; and perform facial recognition processing on the image including avoiding facial recognition processing in the potential spoofing region to increase processing efficiency.

2. The system of claim 1 , wherein the pattern is moving.

3. The system of claim 1 , wherein the pattern includes a foreground and a background.

4. The system of claim 3 , wherein the background is selected to illuminate the face for the authentication attempt.

5. The system of claim 1 , comprising a library controller to: receive a user submitted pattern; and test the user submitted pattern to determine whether it as features to distinguish it from organic features.

6. The system of claim 5 , wherein the spoofing controller is arranged to include the user submitted pattern in a library of patterns when it does have features to distinguish the user submitted pattern from organic features, and rejecting the user submitted pattern otherwise.

7. The system of claim 5 , wherein the library controller is arranged to: add features that are distinguishable from organic features to the user submitted pattern to create a modified user submitted pattern; and add the modified user submitted pattern o the library of patterns.

8. The system of claim 1 , wherein to identify a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image includes the spoofing controller arranged to: find the pattern across a plurality of images, including the image; measure a signal-to-noise ratio for a region in which the pattern was previously found, across the plurality of images; and make the region the potential spoofing region when the signal-to-noise ratio is beyond a threshold.

9. A machine-implemented method to prevent face-based authentication spoofing, the method comprising: controlling a visible light emitter to project a pattern into a field of view for a camera during an authentication attempt using a face; obtaining an image from the camera for the authentication attempt; identifying a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image; and performing facial recognition processing on the image including avoiding facial recognition processing in the potential spoofing region to increase processing efficiency.

10. The method of claim 9 , wherein controlling the visible light emitter to project the pattern comprises projecting the pattern with motion.

11. The method of claim 9 , wherein the pattern includes a foreground and a background.

12. The method of claim 11 , wherein the background is selected to illuminate the face for the authentication attempt.

13. The method of claim 9 , comprising: receiving a user submitted pattern; and testing the user submitted pattern to determine whether it has features to distinguish it from organic features.

14. The method of claim 13 , comprising including the user submitted pattern in a library of patterns when it does have features to distinguish the user submitted pattern from organic features, and rejecting the user submitted pattern otherwise.

15. The method of claim 13 , comprising: adding features that are distinguishable from organic features to the user submitted pattern to create a modified user submitted pattern; and adding the modified user submitted pattern to the library of patterns.

16. The method of claim 9 , wherein identifying a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image includes: finding the pattern across a plurality of images, including the image; measuring a signal-to-noise ratio for a region in which the pattern was previously found, across the plurality of images; and making the region the potential spoofing region when the signal-to-noise ratio is beyond a threshold.

17. At least one non-transitory machine readable medium including instructions stored thereon to prevent face-based authentication spoofing, the instructions, when executed by a machine, cause the machine to perform operations comprising: controlling a visible light emitter to project a pattern into a field of view for a camera during an authentication attempt using a face; obtaining an image from the camera for the authentication attempt; identifying a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image; and performing facial recognition processing on the image including avoiding facial recognition processing in the potential spoofing region to increase processing efficiency.

18. The at least one non-transitory machine readable medium of claim 17 , wherein the pattern is moving.

19. The at least one non-transitory machine readable medium of claim 17 , wherein the pattern includes a foreground and a background.

20. The at least one non-transitory machine readable medium of claim 19 , wherein the background is selected to illuminate the face for the authentication attempt.

21. The at least one non-transitory machine readable medium of claim 17 , comprising: receiving a user submitted pattern; and testing the user submitted pattern to determine whether it has features to distinguish it from organic features.

22. The at least one non-transitory machine readable medium of claim 21 , comprising including the user submitted pattern in a library of patterns when it does have features to distinguish it from organic features, and rejecting the user submitted pattern otherwise.

23. The at least one non-transitory machine readable medium of claim 21 , comprising: adding features that are distinguishable from organic features to the user submitted pattern to create a modified user submitted pattern; and putting the modified user submitted pattern to the library of patterns.

24. The at least one non-transitory machine readable medium of claim 17 , wherein identifying a potential spoofing region of the image by finding the pattern within predetermined tolerances in the image includes: finding the pattern across a plurality of images, including the image; measuring a signal-to-noise ratio for a region in which the pattern was previously found, across the plurality of images; and making the region the potential spoofing region when the signal-to-noise ratio is beyond a threshold.